Class I and II aaRS recognition of opposite grooves was likely among the earliest determinants fixed in the tRNA acceptor stem bases. A new regression model identifies those determinants in bacterial tRNAs. Integral coefficients relate digital dependent to independent variables with perfect agreement between observed and calculated grooves for all twenty isoaccepting tRNAs. Recognition is mediated by the Discriminator base 73, the first base pair, and base 2 of the acceptor stem. Subsets of these coefficients also identically compute grooves recognized by smaller numbers of aaRS. Thus, the model is hierarchical, suggesting that new rules were added to pre-existing ones as new amino acids joined the coding alphabet. A thermodynamic rationale for the simplest model implies that Class-dependent aaRS secondary structures exploited differential tendencies of the acceptor stem to form the hairpin observed in Class I aaRS•tRNA complexes, enabling the earliest groove discrimination. Curiously, groove recognition also depends explicitly on the identity of base 2 in a manner consistent with the middle bases of the codon table, confirming a hidden ancestry of codon-anticodon pairing in the acceptor stem. That, and the lack of correlation with anticodon bases support prior productive coding interaction of tRNA minihelices with proto-mRNA.

sábado, julho 28, 2018

There Was No Big Bang Singularity

Starts With A Bang

Ethan Siegel Contributor

Jul 27, 2018, 10:00am

An illustration of our cosmic history, from the Big Bang until the present, within the context of the expanding Universe. The hot Big Bang was preceded by a state of cosmic inflation, but the idea that all of it must be preceded by a singularity is woefully out of date.NASA / WMAP SCIENCE TEAM

Almost everyone has heard the story of the Big Bang. But if you ask anyone, from a layperson to a cosmologist, to finish the following sentence, "In the beginning, there was..." you'll get a slew of different answers. One of the most common ones is "a singularity," which refers to an instant where all the matter and energy in the Universe was concentrated into a single point. The temperatures, densities, and energies of the Universe would be arbitrarily, infinitely large, and could even coincide with the birth of time and space itself.

But this picture isn't just wrong, it's nearly 40 years out of date! We are absolutely certain there was no singularity associated with the hot Big Bang, and there may not have even been a birth to space and time at all. Here's what we know and how we know it.

When we look out at the Universe today, we see that it's full of galaxies in all directions at a wide variety of distances. On average, we also find that the more distant a galaxy is, the faster it appears to be receding from us. This isn't due to the actual motions of the individual galaxies through space, though; it's due to the fact that the fabric of space itself is expanding.

This was a prediction that was first teased out of General Relativity in 1922 by Alexander Friedmann, and was observationally confirmed by the work of Edwin Hubble and others in the 1920s. It means that, as time goes on, the matter within it spreads out and becomes less dense, since the volume of the Universe increases. It also means that, if we look to the past, the Universe was denser, hotter, and more uniform.

There is a pernicious temptation in science to speak authoritatively about topics that are beyond scientific exploration and certainty. This has led some theoretical physicists to advocate for a “post-empirical” form of science. That is the idea that theories need not be judged on their ability to make new and testable predictions about the observable universe, in some cases, the absence of a plausible alternative is sufficient. One might be forgiven if one sees an analogous situation in biology, specifically when it comes to the origin(s) of life on Earth or elsewhere, and the steps behind major, essentially historical evolutionary events. For example, there are almost daily reports (and rather excited press releases) of how some scientific observations argue for the plausibility of life on other planets, in other solar systems, or in other galaxies, when in fact, what has been found is one or another organic molecule, or hints of organic material, in meteorites and comets. Rarely is the fact that we have yet to find life anywhere but here on Earth mentioned explicitly.

In a world in which magical thinking persists in popular culture, as witness the number of prominent public figures who speak out against vaccination, advocate unproven, “natural” treatments for (currently) medically incurable diseases, make claims for a flat Earth, or advocate for the insertion of jade eggs to strengthen vaginal muscles, there is a serious challenge to the scientific community as to how to maintain an appreciation for established scientific conclusions and to convey the underlying logic of the scientific enterprise.

In the context of origin-of-life studies, a key is to explicitly recognize the constraints under which science operates. In contrast to the quote from Jack Szostak and colleagues in a 2001 Nature article, “Defining life is notoriously difficult; its very diversity resists the confines of any compact definition,” the real problem is that the diversity of life, as we know it, is superficial and something of an illusion—we know of only one type of life, one original organism, and all of the subsequent organisms derived from it by various evolutionary processes. Moreover, we cannot examine this “last universal common ancestor” or LUCA, although there is no scientific doubt that A) it existed, B) it used DNA to store information, C) information was expressed in the form of RNAs, many of which, in turn, encoded polypeptides/proteins, D) it was bounded by a lipid membrane, and F) it can be characterized as a nonequilibrium reaction system, one that has been running continuously for billions of years and whose descendants are present in every living cell since (see my 2010 article on the topic).

LUCA was pretty complex, with the machinery to maintain its nonequilibrium state, a specific nucleotide-to-polypeptide coding scheme, and the ability to carry out DNA replication, transcription factor–regulated RNA synthesis, and ribosome-mediated, RNA-directed polypeptide synthesis. We might go a little further, and speculate that LUCA arose in a special environmental niche, and given its membrane-nature, likely an iso-osmotic one. The evolutionary adaption of a cell wall to deal with hypo- and hyper-osmotic conditions was likely an early (post-LUCA) innovation that allowed the spread and diversification of proto-bacteria and proto-archaea to more osmotically challenging environments—perhaps driven in part to escape wall-less predators, as proposed by Patrick Forterre of the Institut Pasteur.

But what came before and the exact steps leading to LUCA are unknowable. Moreover, the billions of years that have elapsed since LUCA’s origin and the active nature of evolutionary processes that result in new genes “popping out” of the noise and becoming essential in organisms from fruit flies to humans, combined with the reality of structural or functional convergences, the growing recognition of small and alternative open reading frames that encode functionally different proteins, and the ubiquity of various forms of horizontal gene transfer, means that historic details and their evolutionary drivers are often obscure.

quarta-feira, julho 18, 2018

Dependency graph illustrating the module jsdom accessing the module request which accesses other modules. Request is also accessed by other higher-level modules.

Abstract

The hierarchical classification of life has been claimed as compelling evidence for universal common ancestry. However, research has uncovered much data which is not congruent with the hierarchical pattern. Nevertheless, biological data resembles a nested hierarchy sufficiently well to require an explanation. While many defenders of intelligent design dispute common descent, no alternative account of the approximate nested hierarchy pattern has been widely adopted. We present the dependency graph hypothesis as an alternative explanation, based on the technique used by software developers to reuse code among different software projects. This hypothesis postulates that different biological species share modules related by a dependency graph. We evaluate several predictions made by this model about both biological and synthetic data, finding them to be fulfilled.

We present the first known fossilized snake embryo/neonate preserved in early Late Cretaceous (Early Cenomanian) amber from Myanmar, which at the time, was an island arc including terranes from Austral Gondwana. This unique and very tiny snake fossil is an articulated postcranial skeleton, which includes posterior precloacal, cloacal, and caudal vertebrae, and details of squamation and body shape; a second specimen preserves a fragment of shed skin interpreted as a snake. Important details of skeletal ontogeny, including the stage at which snake zygosphene-zygantral joints began to form along with the neural arch lamina, are preserved. The vertebrae show similarities to those of fossil Gondwanan snakes, suggesting a dispersal route of Gondwanan faunas to Laurasia. Finally, the new species is the first Mesozoic snake to be found in a forested environment, indicating greater ecological diversity among early snakes than previously thought.

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

Four ways to study mutation rate, a crucial statistic in studies of evolution

Jul 1, 2018

AMBER DANCE

Mutation: it’s the raw material for evolution. That makes knowing the rate at which it occurs crucial to the study of evolutionary biology.

Mutation rate figures into all kinds of calculations. For example, the “molecular clocks” that evolutionary biologists use to estimate when one species first diverged into two are based on species’ mutation rates. Scientists also use the rates to track how quickly viruses, such as influenza, evolve. And cancer biologists are interested in using mutation rates to estimate how quickly tumor cell genomes might change over time.

“It is a parameter that you have to input into every mutation-evolution model there is,” says Yuan Zhu, a postdoc at the Genome Institute of Singapore.

Scientists used to infer mutations from phenotypic changes, such as the development of drug resistance. Now, thanks to increasingly cost-effective and rapid DNA sequencing, more-sophisticated ways of getting a handle on whole-genome mutation rates have emerged. Among these techniques are methods that researchers can apply to just about any species. Though scientists have primarily analyzed microbes and viruses thus far, they’ve also tackled lab models such as Drosophila and Arabidopsis, and even humans. These techniques are revealing how the mutation rate varies across the genome of a single species, and they’re pinpointing regions that are especially prone to alteration. They’re also uncovering the error rates of different enzymes, such as polymerases and repair enzymes, in the DNA replication process.

Here, The Scientist profiles four different ways of studying mutation rates in viruses, yeasts, and humans.

We perform a detailed analysis of the migratory motion of human embryonic stem cells in two-dimensions, both when isolated and in close proximity to another cell, recorded with time-lapse microscopic imaging. We show that isolated cells tend to perform an unusual locally anisotropic walk, moving backwards and forwards along a preferred local direction correlated over a timescale of around 50 min and aligned with the axis of the cell elongation. Increasing elongation of the cell shape is associated with increased instantaneous migration speed. We also show that two cells in close proximity tend to move in the same direction, with the average separation of m or less and the correlation length of around 25 μm, a typical cell diameter. These results can be used as a basis for the mathematical modelling of the formation of clonal hESC colonies.

Fruit flies exhibit sexual dimorphism. Males are smaller, they have bristle on their forelegs, their abdomen is blunt, and their stripes meld together and become dark toward the back of the abdomen. Females are larger, and their abdomen is longer, pointed, and striped until the end. The sexes differ in many aspects. In this study, researchers reveal that male fruit flies respond to environmental temperatures differently than females that bear the same mtDNA variant.

Mitochondria are essential organelles, found within eukaryotic cells, which contain their own DNA. Mitochondrial DNA (mtDNA) has traditionally been used in population genetic and biogeographic studies as a maternally-inherited and evolutionary-neutral genetic marker. However, it is now clear that polymorphisms within the mtDNA sequence are routinely non-neutral, and furthermore several studies have suggested that such mtDNA polymorphisms are also sensitive to thermal selection. These observations led to the formulation of the “mitochondrial climatic adaptation” hypothesis, for which all published evidence to date is correlational. Here, we use laboratory-based experimental evolution in the fruit fly, Drosophila melanogaster, to test whether thermal selection can shift population frequencies of two mtDNA haplogroups whose natural frequencies exhibit clinal associations with latitude along the Australian east-coast. We present experimental evidence that the thermal regime in which the laboratory populations were maintained drove changes in haplogroup frequencies across generations. Our results strengthen the emerging view that intra-specific mtDNA variants are sensitive to selection, and suggest spatial distributions of mtDNA variants in natural populations of metazoans might reflect adaptation to climatic environments rather than within-population coalescence and diffusion of selectively-neutral haplotypes across populations.

Acknowledgements

We thank Vanessa Kellerman and Winston Yee for assistance with wild sample collection, and Mary Ann Price, Carla Sgrò, Ritsuko Suyama, Garth Illsley, Richard Lee, Nicholas Luscombe, Pavel Munclinger, Takeshi Noda, and Oleg Simakov for helpful advice. We thank Yuan Liu for her assistance with artwork design. This work was supported by the Physics and Biology Unit of the Okinawa Institute of Science and Technology Graduate University (J.M.) and JSPS P12751 + 24 2751 to Z.L. and J.M., the Hermon-Slade Foundation (HSF 15/2) and the Australian Research Council (FT160100022 and DP170100165) to D.K.D. Initial stages of the study were funded by Go8EURFA11 2011003556 to Z.L. and D.K.D.

Z.L. and D.K.D. designed the experiment. Z.L. performed the experiment. Z.L. and M.F.C. provided mitogenomic sequences. Z.L., R.P., D.K.D., M.F.C. and J.M. contributed to the data analyses. Z.L., D.K.D., R.P., J.M. and M.F.C. wrote the manuscript.

CRISPR–Cas9 is poised to become the gene editing tool of choice in clinical contexts. Thus far, exploration of Cas9-induced genetic alterations has been limited to the immediate vicinity of the target site and distal off-target sequences, leading to the conclusion that CRISPR–Cas9 was reasonably specific. Here we report significant on-target mutagenesis, such as large deletions and more complex genomic rearrangements at the targeted sites in mouse embryonic stem cells, mouse hematopoietic progenitors and a human differentiated cell line. Using long-read sequencing and long-range PCR genotyping, we show that DNA breaks introduced by single-guide RNA/Cas9 frequently resolved into deletions extending over many kilobases. Furthermore, lesions distal to the cut site and crossover events were identified. The observed genomic damage in mitotically active cells caused by CRISPR–Cas9 editing may have pathogenic consequences.

The mutation–selection process is the most fundamental mechanism of evolution. In 1935, R. A. Fisher proved his fundamental theorem of natural selection, providing a model in which the rate of change of mean fitness is equal to the genetic variance of a species. Fisher did not include mutations in his model, but believed that mutations would provide a continual supply of variance resulting in perpetual increase in mean fitness, thus providing a foundation for neo-Darwinian theory. In this paper we re-examine Fisher’s Theorem, showing that because it disregards mutations, and because it is invalid beyond one instant in time, it has limited biological relevance. We build a differential equations model from Fisher’s first principles with mutations added, and prove a revised theorem showing the rate of change in mean fitness is equal to genetic variance plus a mutational effects term. We refer to our revised theorem as the fundamental theorem of natural selection with mutations. Our expanded theorem, and our associated analyses (analytic computation, numerical simulation, and visualization), provide a clearer understanding of the mutation–selection process, and allow application of biologically realistic parameters such as mutational effects. The expanded theorem has biological implications significantly different from what Fisher had envisioned.

This book is intended as an introduction to a wide variety of biases affecting human cognition, with a specific focus on how they affect scientists and the communication of science. A significant point, however, should be made up front: scientists are people and the biases that are discussed herein are, for the most part, generic in that they affect people in general rather than being specific to any particular group of people. That is, the decision making biases of experts and specialists tend to be more similar to those of lay-people than different (although chapter 10 will discuss situations where that is not the case). The role of this book, therefore, is to lay out how these common biases affect the specific types of judgements, decisions and communications made by scientists.

The book is divided into four parts. The first (chapters 1–3), introduces the reader to a variety of decision biases, the field of decision making in general and fundamental considerations regarding the psychology underlying different types of communication.

Each chapter in the second part of the book (chapters 4–10) will focus on a specific bias or a set of related decision making tendencies, describing the general effect, how they impact decisions and some of the implications for scientists’ decisions and communications.

Part 3 (chapters 11–13) brings insights about these individual biases together to demonstrate how they can combine and interact to produce a variety of welldocumented effects, including publication bias and stubborn denial of what, to scientists, are regarded as accepted facts. It also covers, more broadly, the ways in which biases can be overcome or avoided.

Finally, part 4 (chapter 14) draws overall conclusions about the impact of biases on science and communication, with advice on how best to move forward given what we know about their modes of action and amelioration strategies.

In all cases, an effort has been made to ensure that the latest information is incorporated and, where there are disputes or disagreements over the causes or nature of biases, alternative views are noted for those interested in following up in greater detail.

Each chapter also includes advice or exercises to help readers to identify or reduce biases in their own thinking.

domingo, julho 15, 2018

Ontology, Causality, and Methodology of Evolutionary Research Programs

Otsuka, Jun (2018)

Source/Fonte: University of Arkansas

Abstract

Scientific conflicts often stem from differences in the conceptual framework through which scientists view and understand their own field. In this chapter, I analyze the ontological and methodological assumptions of three traditions in evolutionary biology, namely, Ernst Mayr’s population thinking, the gene-centered view of the Modern Syn thesis (MS), and the Extended Evolutionary Synthesis (EES). Each of these frameworks presupposes a different account of "evolutionary causes," and this discrepancy prevents mutual understanding and objective evaluation in the recent contention surrounding the EES. From this perspective, the chapter characterizes the EES research program as an attempt to introduce causal structures beyond genes as additional units of evolution, and compares its research methodology and objectives with those of the traditional MS framework.

The copepod Tigriopus californicus shows extensive population divergence and is becoming a model for understanding allopatric differentiation and the early stages of speciation. Here, we report a high-quality reference genome for one population (~190 megabases across 12 scaffolds, and ~15,500 protein-coding genes). Comparison with other arthropods reveals 2,526 genes presumed to be specific to T. californicus, with an apparent proliferation of genes involved in ion transport and receptor activity. Beyond the reference population, we report re-sequenced genomes of seven additional populations, spanning the continuum of reproductive isolation. Populations show extreme mitochondrial DNA divergence, with higher levels of amino acid differentiation than observed in other taxa. Across the nuclear genome, we find elevated protein evolutionary rates and positive selection in genes predicted to interact with mitochondrial DNA and the proteins and RNA it encodes in multiple pathways. Together, these results support the hypothesis that rapid mitochondrial evolution drives compensatory nuclear evolution within isolated populations, thereby providing a potentially important mechanism for causing intrinsic reproductive isolation.

Acknowledgements

This work was supported by US National Science Foundation grants (IOS1154321 to S.E.; IOS1155030 to R.S.B.; and IOS1155325 to C.S.W.) and Oregon State University faculty startup funds to F.S.B. The authors thank S. Morgan and R. J. Pereira for help with sample collection.

The view that Homo sapiens evolved from a single region/population within Africa has been given primacy in studies of human evolution.

However, developments across multiple fields show that relevant data are no longer consistent with this view

We argue instead that Homo sapiens evolved within a set of interlinked groups living across Africa, whose connectivity changed through time.

Genetic models therefore need to incorporate a more complex view of ancient migration and divergence in Africa.

We summarize this new framework emphasizing population structure, outline how this changes our understanding of human evolution, and identify new research directions.

We challenge the view that our species, Homo sapiens, evolved within a single population and/or region of Africa. The chronology and physical diversity of Pleistocene human fossils suggest that morphologically varied populations pertaining to the H. sapiens clade lived throughout Africa. Similarly, the African archaeological record demonstrates the polycentric origin and persistence of regionally distinct Pleistocene material culture in a variety of paleoecological settings. Genetic studies also indicate that present-day population structure within Africa extends to deep times, paralleling a paleoenvironmental record of shifting and fractured habitable zones. We argue that these fields support an emerging view of a highly structured African prehistory that should be considered in human evolutionary inferences, prompting new interpretations, questions, and interdisciplinary research directions.

A Different View of African Origins

The lineage of Homo sapiens probably originated in Africa at least ∼500 thousand years ago (ka) [1], and the earliest observed morphological manifestations of this clade appeared by ∼300 ka [2]. Early H. sapiens fossils do not demonstrate a simple linear progression towards contemporary human morphology. Instead, putative early H. sapiens remains exhibit remarkable morphological diversity and geographical spread. Together with recent archaeological and genetic lines of evidence, these data are consistent with the view that our species originated and diversified within strongly subdivided (i.e., structured) populations, probably living across Africa, that were connected by sporadic gene flow [1, 3, 4, 5, 6, 7, 8]. This concept of ‘African multiregionalism’ [1] may also include hybridization between H. sapiens and more divergent hominins (see Glossary) living in different regions [1, 9, 10, 11, 12]. Crucially, such population subdivisions may have been shaped and sustained by shifts in ecological boundaries [7, 13, 14], challenging the view that our species was endemic to a single region or habitat, and implying an often underacknowledged complexity to our African origins.

In this paper we examine and synthesize fossil, archaeological, genetic, and paleoenvironmental data to refine our understanding of the time-depth, character, and maintenance of Pleistocene population structure. In doing so, we attempt to separate data from inference to stress that using models of population structure fundamentally changes interpretations of recent human evolution.

The Morphological Diversity and Spread of the Homo sapiens Clade

The constellation of morphological features characterizing H. sapiens is debated. This has strongly impacted on interpretations of recent human origins by variably including or excluding different fossils from interpretative analyses. For example, different morphological criteria and analytical methods have been used to support both a gradual, mosaic-like process of modernization of our species or, conversely, a punctuated speciation (e.g., [1]).

Extant human crania are characterized by a combination of features that distinguish us from our fossil relatives and ancestors, such as a small and gracile face, a chin, and a globular braincase. However, these typical modern human features emerge in a mosaic-like fashion within the H. sapiens clade. The oldest currently recognized members of the H. sapiens clade, from Jebel Irhoud in North Africa, have a facial morphology very similar to extant H. sapiens, as well as endocranial volumes that fall within the contemporary range of variation [2]. However, their braincase shapes are elongated rather than globular, suggesting that distinctive features of brain shape, and possibly brain function, evolved within H. sapiens [2, 5] (Figure 1). Other early H. sapiens fossils from Florisbad in South Africa (∼260 ka), Omo Kibish (∼195 ka) and Herto (∼160 ka), both in Ethiopia, are morphologically diverse [1, 16]. This diversity has led some researchers to propose that fossils such as Jebel Irhoud and Florisbad actually represent a more primitive species called ‘H. helmei’, using the binomen given to the Florisbad partial cranium in 1935 [17, 18]. In a similar vein, the fossil crania from Herto [19], which combine a relatively globular braincase with a robust occipital and large face, were described as the subspecies H. sapiens idaltu because they fall outside the variation of recent humans.

However, we view H. sapiens as an evolving lineage with deep African roots, and therefore prefer to recognize such fossils as part of the diversity shown by early members of the H. sapiens clade. The full suite of cranial features characterizing contemporary humans does not appear until fairly recently, between about ∼100–40 ka [20]. The character and chronology of early H. sapiens fossils, together with their geographic distribution across Africa, suggests that evolution may at times have progressed independently in different regions, in populations that were often semi-isolated for millennia by distance and/or ecological barriers, such as hyperarid regions or tropical forests.

Further insights into the geographic extent and potential habitat diversity of early H. sapiens populations can be gained from more recent forager populations in Africa, which were also strongly structured. For example, Later Stone Age (LSA) human remains highlight both the retention of ‘archaic’ traits and the maintenance of considerable morphological diversity into the terminal Pleistocene [11, 21]. In the Holocene, the skeletal record becomes much richer, but there remains considerable spatial variation in morphology. Variation between populations in different regions and environments of Africa may have been shaped by isolation-by-distance and local environmental adaptations [22, 23, 24, 25, 26]. For example, challenging environments (e.g., deserts, rainforest) and isolation have likely played a significant role in shaping the population structure of Holocene African foragers and isolated hunter-gatherers across the tropics [25, 27].

Ultimately, the processes underlying the emergence of any ‘package’ of derived features diagnostic of early H. sapiens anatomy remain incompletely understood. However, the data do not seem to be consistent with the long-held view that human ancestry is derived predominantly from a single African region hosting a panmictic population. Instead, H. sapiens likely descended from a shifting structured population (i.e., a set of interlinked groups whose connectivity changed through time), each exhibiting different characteristics of anatomical ‘modernity’. The discovery that the primitive-looking H. naledi dates to between ∼335 ka and 236 ka [28], and that the Broken Hill 1 Homo heidelbergensis skull may date to ∼300–125 ka [29], also shows that other hominin species in Africa coexisted with H. sapiens, raising the possibility of African archaic interbreeding. Future research should attempt to determine which features evolved before the appearance of our species and which primarily developed within the evolutionary history of our species. Another key area concerns understanding the extent to which different processes shaped observed changes. For example, the narrowing of the pelvis may reflect different processes including neutral genetic drift, adaptation to ecological variation, and life-history variation.

Three brain scans (from the front, side and above) of two different brains (pictured on the left and on the right) belonging to twins. The furrows and ridges are different in each person.

Credit: Lutz Jaencke, UZH

Abstract

We examined whether it is possible to identify individual subjects on the basis of brain anatomical features. For this, we analyzed a dataset comprising 191 subjects who were scanned three times over a period of two years. Based on FreeSurfer routines, we generated three datasets covering 148 anatomical regions (cortical thickness, area, volume). These three datasets were also combined to a dataset containing all of these three measures. In addition, we used a dataset comprising 11 composite anatomical measures for which we used larger brain regions (11LBR). These datasets were subjected to a linear discriminant analysis (LDA) and a weighted K-nearest neighbors approach (WKNN) to identify single subjects. For this, we randomly chose a data subset (training set) with which we calculated the individual identification. The obtained results were applied to the remaining sample (test data). In general, we obtained excellent identification results (reasonably good results were obtained for 11LBR using WKNN). Using different data manipulation techniques (adding white Gaussian noise to the test data and changing sample sizes) still revealed very good identification results, particularly for the LDA technique. Interestingly, using the small 11LBR dataset also revealed very good results indicating that the human brain is highly individual.

Acknowledgements

The current analysis incorporates data from the Longitudinal Healthy Aging Brain (LHAB) database project, which is carried out as one of the core projects at the International Normal Aging and Plasticity Imaging Center/INAPIC and the University Research Priority Program “Dynamics of Healthy Aging” of the University of Zurich. This work was supported by the Velux Stiftung (project No. 369), by the University Research Priority Program “Dynamics of Healthy Aging” of the University of Zurich. We would also like to thank professor Carolin Strobl (Department of Psychology, University of Zurich) and professor Robert Riener (Department of Health Sciences and Technology, ETH Zurich) for their contribution to this paper. All subjects gave written informed consent prior to participating in the study. In addition, all methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by the ethical committee of the canton of Zurich (KEK-ZH-Nr. 2010–0267).

Author information

Affiliations

Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland

International Normal Aging and Plasticity Imaging Center (INAPIC), University of Zurich, Zurich, Switzerland

Susan Mérillat & Lutz Jäncke

University Research Priority Program (URPP) “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland

Franziskus Liem, Susan Mérillat & Lutz Jäncke

Contributions

S.V. wrote the Matlab code, conducted the analyses, interpreted the data, prepared figures, and wrote the main manuscript; L.J. participated in data analysis, design of the study, interpretation, and writing of the manuscript; F.L. S.M., J.H. participated in interpretation and writing of the manuscript.

Competing Interests

The authors declare no competing interests.

Corresponding author

Correspondence to Lutz Jäncke.

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